1 2 #include "src/mat/impls/baij/mpi/mpibaij.h" /*I "petscmat.h" I*/ 3 #include "mpisbaij.h" 4 #include "src/mat/impls/sbaij/seq/sbaij.h" 5 6 EXTERN PetscErrorCode MatSetUpMultiply_MPISBAIJ(Mat); 7 EXTERN PetscErrorCode MatSetUpMultiply_MPISBAIJ_2comm(Mat); 8 EXTERN PetscErrorCode DisAssemble_MPISBAIJ(Mat); 9 EXTERN PetscErrorCode MatIncreaseOverlap_MPISBAIJ(Mat,PetscInt,IS[],PetscInt); 10 EXTERN PetscErrorCode MatGetValues_SeqSBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []); 11 EXTERN PetscErrorCode MatGetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []); 12 EXTERN PetscErrorCode MatSetValues_SeqSBAIJ(Mat,PetscInt,const PetscInt [],PetscInt,const PetscInt [],const PetscScalar [],InsertMode); 13 EXTERN PetscErrorCode MatSetValuesBlocked_SeqSBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 14 EXTERN PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 15 EXTERN PetscErrorCode MatGetRow_SeqSBAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**); 16 EXTERN PetscErrorCode MatRestoreRow_SeqSBAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**); 17 EXTERN PetscErrorCode MatPrintHelp_SeqSBAIJ(Mat); 18 EXTERN PetscErrorCode MatZeroRows_SeqSBAIJ(Mat,IS,PetscScalar*); 19 EXTERN PetscErrorCode MatZeroRows_SeqBAIJ(Mat,IS,PetscScalar *); 20 EXTERN PetscErrorCode MatGetRowMax_MPISBAIJ(Mat,Vec); 21 EXTERN PetscErrorCode MatRelax_MPISBAIJ(Mat,Vec,PetscReal,MatSORType,PetscReal,PetscInt,PetscInt,Vec); 22 23 /* UGLY, ugly, ugly 24 When MatScalar == PetscScalar the function MatSetValuesBlocked_MPIBAIJ_MatScalar() does 25 not exist. Otherwise ..._MatScalar() takes matrix elements in single precision and 26 inserts them into the single precision data structure. The function MatSetValuesBlocked_MPIBAIJ() 27 converts the entries into single precision and then calls ..._MatScalar() to put them 28 into the single precision data structures. 29 */ 30 #if defined(PETSC_USE_MAT_SINGLE) 31 EXTERN PetscErrorCode MatSetValuesBlocked_SeqSBAIJ_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode); 32 EXTERN PetscErrorCode MatSetValues_MPISBAIJ_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode); 33 EXTERN PetscErrorCode MatSetValuesBlocked_MPISBAIJ_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode); 34 EXTERN PetscErrorCode MatSetValues_MPISBAIJ_HT_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode); 35 EXTERN PetscErrorCode MatSetValuesBlocked_MPISBAIJ_HT_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode); 36 #else 37 #define MatSetValuesBlocked_SeqSBAIJ_MatScalar MatSetValuesBlocked_SeqSBAIJ 38 #define MatSetValues_MPISBAIJ_MatScalar MatSetValues_MPISBAIJ 39 #define MatSetValuesBlocked_MPISBAIJ_MatScalar MatSetValuesBlocked_MPISBAIJ 40 #define MatSetValues_MPISBAIJ_HT_MatScalar MatSetValues_MPISBAIJ_HT 41 #define MatSetValuesBlocked_MPISBAIJ_HT_MatScalar MatSetValuesBlocked_MPISBAIJ_HT 42 #endif 43 44 EXTERN_C_BEGIN 45 #undef __FUNCT__ 46 #define __FUNCT__ "MatStoreValues_MPISBAIJ" 47 PetscErrorCode MatStoreValues_MPISBAIJ(Mat mat) 48 { 49 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data; 50 PetscErrorCode ierr; 51 52 PetscFunctionBegin; 53 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 54 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 55 PetscFunctionReturn(0); 56 } 57 EXTERN_C_END 58 59 EXTERN_C_BEGIN 60 #undef __FUNCT__ 61 #define __FUNCT__ "MatRetrieveValues_MPISBAIJ" 62 PetscErrorCode MatRetrieveValues_MPISBAIJ(Mat mat) 63 { 64 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data; 65 PetscErrorCode ierr; 66 67 PetscFunctionBegin; 68 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 69 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 70 PetscFunctionReturn(0); 71 } 72 EXTERN_C_END 73 74 75 #define CHUNKSIZE 10 76 77 #define MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv) \ 78 { \ 79 \ 80 brow = row/bs; \ 81 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 82 rmax = aimax[brow]; nrow = ailen[brow]; \ 83 bcol = col/bs; \ 84 ridx = row % bs; cidx = col % bs; \ 85 low = 0; high = nrow; \ 86 while (high-low > 3) { \ 87 t = (low+high)/2; \ 88 if (rp[t] > bcol) high = t; \ 89 else low = t; \ 90 } \ 91 for (_i=low; _i<high; _i++) { \ 92 if (rp[_i] > bcol) break; \ 93 if (rp[_i] == bcol) { \ 94 bap = ap + bs2*_i + bs*cidx + ridx; \ 95 if (addv == ADD_VALUES) *bap += value; \ 96 else *bap = value; \ 97 goto a_noinsert; \ 98 } \ 99 } \ 100 if (a->nonew == 1) goto a_noinsert; \ 101 else if (a->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 102 if (nrow >= rmax) { \ 103 /* there is no extra room in row, therefore enlarge */ \ 104 PetscInt new_nz = ai[a->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 105 MatScalar *new_a; \ 106 \ 107 if (a->nonew == -2) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col); \ 108 \ 109 /* malloc new storage space */ \ 110 len = new_nz*(sizeof(PetscInt)+bs2*sizeof(MatScalar))+(a->mbs+1)*sizeof(PetscInt); \ 111 ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); \ 112 new_j = (PetscInt*)(new_a + bs2*new_nz); \ 113 new_i = new_j + new_nz; \ 114 \ 115 /* copy over old data into new slots */ \ 116 for (ii=0; ii<brow+1; ii++) {new_i[ii] = ai[ii];} \ 117 for (ii=brow+1; ii<a->mbs+1; ii++) {new_i[ii] = ai[ii]+CHUNKSIZE;} \ 118 ierr = PetscMemcpy(new_j,aj,(ai[brow]+nrow)*sizeof(PetscInt));CHKERRQ(ierr); \ 119 len = (new_nz - CHUNKSIZE - ai[brow] - nrow); \ 120 ierr = PetscMemcpy(new_j+ai[brow]+nrow+CHUNKSIZE,aj+ai[brow]+nrow,len*sizeof(PetscInt));CHKERRQ(ierr); \ 121 ierr = PetscMemcpy(new_a,aa,(ai[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 122 ierr = PetscMemzero(new_a+bs2*(ai[brow]+nrow),bs2*CHUNKSIZE*sizeof(PetscScalar));CHKERRQ(ierr); \ 123 ierr = PetscMemcpy(new_a+bs2*(ai[brow]+nrow+CHUNKSIZE), \ 124 aa+bs2*(ai[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); \ 125 /* free up old matrix storage */ \ 126 ierr = PetscFree(a->a);CHKERRQ(ierr); \ 127 if (!a->singlemalloc) { \ 128 ierr = PetscFree(a->i);CHKERRQ(ierr); \ 129 ierr = PetscFree(a->j);CHKERRQ(ierr);\ 130 } \ 131 aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j; \ 132 a->singlemalloc = PETSC_TRUE; \ 133 \ 134 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 135 rmax = aimax[brow] = aimax[brow] + CHUNKSIZE; \ 136 PetscLogObjectMemory(A,CHUNKSIZE*(sizeof(PetscInt) + bs2*sizeof(MatScalar))); \ 137 a->maxnz += bs2*CHUNKSIZE; \ 138 a->reallocs++; \ 139 a->nz++; \ 140 } \ 141 N = nrow++ - 1; \ 142 /* shift up all the later entries in this row */ \ 143 for (ii=N; ii>=_i; ii--) { \ 144 rp[ii+1] = rp[ii]; \ 145 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 146 } \ 147 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 148 rp[_i] = bcol; \ 149 ap[bs2*_i + bs*cidx + ridx] = value; \ 150 a_noinsert:; \ 151 ailen[brow] = nrow; \ 152 } 153 #ifndef MatSetValues_SeqBAIJ_B_Private 154 #define MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv) \ 155 { \ 156 brow = row/bs; \ 157 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 158 rmax = bimax[brow]; nrow = bilen[brow]; \ 159 bcol = col/bs; \ 160 ridx = row % bs; cidx = col % bs; \ 161 low = 0; high = nrow; \ 162 while (high-low > 3) { \ 163 t = (low+high)/2; \ 164 if (rp[t] > bcol) high = t; \ 165 else low = t; \ 166 } \ 167 for (_i=low; _i<high; _i++) { \ 168 if (rp[_i] > bcol) break; \ 169 if (rp[_i] == bcol) { \ 170 bap = ap + bs2*_i + bs*cidx + ridx; \ 171 if (addv == ADD_VALUES) *bap += value; \ 172 else *bap = value; \ 173 goto b_noinsert; \ 174 } \ 175 } \ 176 if (b->nonew == 1) goto b_noinsert; \ 177 else if (b->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 178 if (nrow >= rmax) { \ 179 /* there is no extra room in row, therefore enlarge */ \ 180 PetscInt new_nz = bi[b->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 181 MatScalar *new_a; \ 182 \ 183 if (b->nonew == -2) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col); \ 184 \ 185 /* malloc new storage space */ \ 186 len = new_nz*(sizeof(PetscInt)+bs2*sizeof(MatScalar))+(b->mbs+1)*sizeof(PetscInt); \ 187 ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); \ 188 new_j = (PetscInt*)(new_a + bs2*new_nz); \ 189 new_i = new_j + new_nz; \ 190 \ 191 /* copy over old data into new slots */ \ 192 for (ii=0; ii<brow+1; ii++) {new_i[ii] = bi[ii];} \ 193 for (ii=brow+1; ii<b->mbs+1; ii++) {new_i[ii] = bi[ii]+CHUNKSIZE;} \ 194 ierr = PetscMemcpy(new_j,bj,(bi[brow]+nrow)*sizeof(PetscInt));CHKERRQ(ierr); \ 195 len = (new_nz - CHUNKSIZE - bi[brow] - nrow); \ 196 ierr = PetscMemcpy(new_j+bi[brow]+nrow+CHUNKSIZE,bj+bi[brow]+nrow,len*sizeof(PetscInt));CHKERRQ(ierr); \ 197 ierr = PetscMemcpy(new_a,ba,(bi[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 198 ierr = PetscMemzero(new_a+bs2*(bi[brow]+nrow),bs2*CHUNKSIZE*sizeof(MatScalar));CHKERRQ(ierr); \ 199 ierr = PetscMemcpy(new_a+bs2*(bi[brow]+nrow+CHUNKSIZE), \ 200 ba+bs2*(bi[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); \ 201 /* free up old matrix storage */ \ 202 ierr = PetscFree(b->a);CHKERRQ(ierr); \ 203 if (!b->singlemalloc) { \ 204 ierr = PetscFree(b->i);CHKERRQ(ierr); \ 205 ierr = PetscFree(b->j);CHKERRQ(ierr); \ 206 } \ 207 ba = b->a = new_a; bi = b->i = new_i; bj = b->j = new_j; \ 208 b->singlemalloc = PETSC_TRUE; \ 209 \ 210 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 211 rmax = bimax[brow] = bimax[brow] + CHUNKSIZE; \ 212 PetscLogObjectMemory(B,CHUNKSIZE*(sizeof(PetscInt) + bs2*sizeof(MatScalar))); \ 213 b->maxnz += bs2*CHUNKSIZE; \ 214 b->reallocs++; \ 215 b->nz++; \ 216 } \ 217 N = nrow++ - 1; \ 218 /* shift up all the later entries in this row */ \ 219 for (ii=N; ii>=_i; ii--) { \ 220 rp[ii+1] = rp[ii]; \ 221 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 222 } \ 223 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 224 rp[_i] = bcol; \ 225 ap[bs2*_i + bs*cidx + ridx] = value; \ 226 b_noinsert:; \ 227 bilen[brow] = nrow; \ 228 } 229 #endif 230 231 #if defined(PETSC_USE_MAT_SINGLE) 232 #undef __FUNCT__ 233 #define __FUNCT__ "MatSetValues_MPISBAIJ" 234 PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 235 { 236 Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)mat->data; 237 PetscErrorCode ierr; 238 PetscInt i,N = m*n; 239 MatScalar *vsingle; 240 241 PetscFunctionBegin; 242 if (N > b->setvalueslen) { 243 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 244 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 245 b->setvalueslen = N; 246 } 247 vsingle = b->setvaluescopy; 248 249 for (i=0; i<N; i++) { 250 vsingle[i] = v[i]; 251 } 252 ierr = MatSetValues_MPISBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 253 PetscFunctionReturn(0); 254 } 255 256 #undef __FUNCT__ 257 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ" 258 PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 259 { 260 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 261 PetscErrorCode ierr; 262 PetscInt i,N = m*n*b->bs2; 263 MatScalar *vsingle; 264 265 PetscFunctionBegin; 266 if (N > b->setvalueslen) { 267 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 268 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 269 b->setvalueslen = N; 270 } 271 vsingle = b->setvaluescopy; 272 for (i=0; i<N; i++) { 273 vsingle[i] = v[i]; 274 } 275 ierr = MatSetValuesBlocked_MPISBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 276 PetscFunctionReturn(0); 277 } 278 279 #undef __FUNCT__ 280 #define __FUNCT__ "MatSetValues_MPISBAIJ_HT" 281 PetscErrorCode MatSetValues_MPISBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 282 { 283 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 284 PetscErrorCode ierr; 285 PetscInt i,N = m*n; 286 MatScalar *vsingle; 287 288 PetscFunctionBegin; 289 SETERRQ(PETSC_ERR_SUP,"Function not yet written for SBAIJ format"); 290 /* PetscFunctionReturn(0); */ 291 } 292 293 #undef __FUNCT__ 294 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ_HT" 295 PetscErrorCode MatSetValuesBlocked_MPISBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 296 { 297 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 298 PetscErrorCode ierr; 299 PetscInt i,N = m*n*b->bs2; 300 MatScalar *vsingle; 301 302 PetscFunctionBegin; 303 SETERRQ(PETSC_ERR_SUP,"Function not yet written for SBAIJ format"); 304 /* PetscFunctionReturn(0); */ 305 } 306 #endif 307 308 /* Only add/insert a(i,j) with i<=j (blocks). 309 Any a(i,j) with i>j input by user is ingored. 310 */ 311 #undef __FUNCT__ 312 #define __FUNCT__ "MatSetValues_MPIBAIJ_MatScalar" 313 PetscErrorCode MatSetValues_MPISBAIJ_MatScalar(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 314 { 315 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 316 MatScalar value; 317 PetscTruth roworiented = baij->roworiented; 318 PetscErrorCode ierr; 319 PetscInt i,j,row,col; 320 PetscInt rstart_orig=baij->rstart_bs; 321 PetscInt rend_orig=baij->rend_bs,cstart_orig=baij->cstart_bs; 322 PetscInt cend_orig=baij->cend_bs,bs=mat->bs; 323 324 /* Some Variables required in the macro */ 325 Mat A = baij->A; 326 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)(A)->data; 327 PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 328 MatScalar *aa=a->a; 329 330 Mat B = baij->B; 331 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 332 PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 333 MatScalar *ba=b->a; 334 335 PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol; 336 PetscInt low,high,t,ridx,cidx,bs2=a->bs2; 337 MatScalar *ap,*bap; 338 339 /* for stash */ 340 PetscInt n_loc, *in_loc=0; 341 MatScalar *v_loc=0; 342 343 PetscFunctionBegin; 344 345 if(!baij->donotstash){ 346 ierr = PetscMalloc(n*sizeof(PetscInt),&in_loc);CHKERRQ(ierr); 347 ierr = PetscMalloc(n*sizeof(MatScalar),&v_loc);CHKERRQ(ierr); 348 } 349 350 for (i=0; i<m; i++) { 351 if (im[i] < 0) continue; 352 #if defined(PETSC_USE_BOPT_g) 353 if (im[i] >= mat->M) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->M-1); 354 #endif 355 if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */ 356 row = im[i] - rstart_orig; /* local row index */ 357 for (j=0; j<n; j++) { 358 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 359 if (in[j] >= cstart_orig && in[j] < cend_orig){ /* diag entry (A) */ 360 col = in[j] - cstart_orig; /* local col index */ 361 brow = row/bs; bcol = col/bs; 362 if (brow > bcol) continue; /* ignore lower triangular blocks of A */ 363 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 364 MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv); 365 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 366 } else if (in[j] < 0) continue; 367 #if defined(PETSC_USE_BOPT_g) 368 else if (in[j] >= mat->N) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->N-1);} 369 #endif 370 else { /* off-diag entry (B) */ 371 if (mat->was_assembled) { 372 if (!baij->colmap) { 373 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 374 } 375 #if defined (PETSC_USE_CTABLE) 376 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 377 col = col - 1; 378 #else 379 col = baij->colmap[in[j]/bs] - 1; 380 #endif 381 if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) { 382 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 383 col = in[j]; 384 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 385 B = baij->B; 386 b = (Mat_SeqBAIJ*)(B)->data; 387 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 388 ba=b->a; 389 } else col += in[j]%bs; 390 } else col = in[j]; 391 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 392 MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv); 393 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 394 } 395 } 396 } else { /* off processor entry */ 397 if (!baij->donotstash) { 398 n_loc = 0; 399 for (j=0; j<n; j++){ 400 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 401 in_loc[n_loc] = in[j]; 402 if (roworiented) { 403 v_loc[n_loc] = v[i*n+j]; 404 } else { 405 v_loc[n_loc] = v[j*m+i]; 406 } 407 n_loc++; 408 } 409 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc);CHKERRQ(ierr); 410 } 411 } 412 } 413 414 if(!baij->donotstash){ 415 ierr = PetscFree(in_loc);CHKERRQ(ierr); 416 ierr = PetscFree(v_loc);CHKERRQ(ierr); 417 } 418 PetscFunctionReturn(0); 419 } 420 421 #undef __FUNCT__ 422 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ_MatScalar" 423 PetscErrorCode MatSetValuesBlocked_MPISBAIJ_MatScalar(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 424 { 425 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 426 const MatScalar *value; 427 MatScalar *barray=baij->barray; 428 PetscTruth roworiented = baij->roworiented; 429 PetscErrorCode ierr; 430 PetscInt i,j,ii,jj,row,col,rstart=baij->rstart; 431 PetscInt rend=baij->rend,cstart=baij->cstart,stepval; 432 PetscInt cend=baij->cend,bs=mat->bs,bs2=baij->bs2; 433 434 PetscFunctionBegin; 435 if(!barray) { 436 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 437 baij->barray = barray; 438 } 439 440 if (roworiented) { 441 stepval = (n-1)*bs; 442 } else { 443 stepval = (m-1)*bs; 444 } 445 for (i=0; i<m; i++) { 446 if (im[i] < 0) continue; 447 #if defined(PETSC_USE_BOPT_g) 448 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1); 449 #endif 450 if (im[i] >= rstart && im[i] < rend) { 451 row = im[i] - rstart; 452 for (j=0; j<n; j++) { 453 /* If NumCol = 1 then a copy is not required */ 454 if ((roworiented) && (n == 1)) { 455 barray = (MatScalar*) v + i*bs2; 456 } else if((!roworiented) && (m == 1)) { 457 barray = (MatScalar*) v + j*bs2; 458 } else { /* Here a copy is required */ 459 if (roworiented) { 460 value = v + i*(stepval+bs)*bs + j*bs; 461 } else { 462 value = v + j*(stepval+bs)*bs + i*bs; 463 } 464 for (ii=0; ii<bs; ii++,value+=stepval) { 465 for (jj=0; jj<bs; jj++) { 466 *barray++ = *value++; 467 } 468 } 469 barray -=bs2; 470 } 471 472 if (in[j] >= cstart && in[j] < cend){ 473 col = in[j] - cstart; 474 ierr = MatSetValuesBlocked_SeqSBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 475 } 476 else if (in[j] < 0) continue; 477 #if defined(PETSC_USE_BOPT_g) 478 else if (in[j] >= baij->Nbs) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1);} 479 #endif 480 else { 481 if (mat->was_assembled) { 482 if (!baij->colmap) { 483 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 484 } 485 486 #if defined(PETSC_USE_BOPT_g) 487 #if defined (PETSC_USE_CTABLE) 488 { PetscInt data; 489 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 490 if ((data - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 491 } 492 #else 493 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 494 #endif 495 #endif 496 #if defined (PETSC_USE_CTABLE) 497 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 498 col = (col - 1)/bs; 499 #else 500 col = (baij->colmap[in[j]] - 1)/bs; 501 #endif 502 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 503 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 504 col = in[j]; 505 } 506 } 507 else col = in[j]; 508 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 509 } 510 } 511 } else { 512 if (!baij->donotstash) { 513 if (roworiented) { 514 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 515 } else { 516 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 517 } 518 } 519 } 520 } 521 PetscFunctionReturn(0); 522 } 523 524 #define HASH_KEY 0.6180339887 525 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(PetscInt)((size)*(tmp-(PetscInt)tmp))) 526 /* #define HASH(size,key) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 527 /* #define HASH(size,key,tmp) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 528 #undef __FUNCT__ 529 #define __FUNCT__ "MatSetValues_MPISBAIJ_HT_MatScalar" 530 PetscErrorCode MatSetValues_MPISBAIJ_HT_MatScalar(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 531 { 532 PetscFunctionBegin; 533 SETERRQ(PETSC_ERR_SUP,"Function not yet written for SBAIJ format"); 534 /* PetscFunctionReturn(0); */ 535 } 536 537 #undef __FUNCT__ 538 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ_HT_MatScalar" 539 PetscErrorCode MatSetValuesBlocked_MPISBAIJ_HT_MatScalar(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 540 { 541 PetscFunctionBegin; 542 SETERRQ(PETSC_ERR_SUP,"Function not yet written for SBAIJ format"); 543 /* PetscFunctionReturn(0); */ 544 } 545 546 #undef __FUNCT__ 547 #define __FUNCT__ "MatGetValues_MPISBAIJ" 548 PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 549 { 550 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 551 PetscErrorCode ierr; 552 PetscInt bs=mat->bs,i,j,bsrstart = baij->rstart*bs,bsrend = baij->rend*bs; 553 PetscInt bscstart = baij->cstart*bs,bscend = baij->cend*bs,row,col,data; 554 555 PetscFunctionBegin; 556 for (i=0; i<m; i++) { 557 if (idxm[i] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); 558 if (idxm[i] >= mat->M) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->M-1); 559 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 560 row = idxm[i] - bsrstart; 561 for (j=0; j<n; j++) { 562 if (idxn[j] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]); 563 if (idxn[j] >= mat->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->N-1); 564 if (idxn[j] >= bscstart && idxn[j] < bscend){ 565 col = idxn[j] - bscstart; 566 ierr = MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 567 } else { 568 if (!baij->colmap) { 569 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 570 } 571 #if defined (PETSC_USE_CTABLE) 572 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 573 data --; 574 #else 575 data = baij->colmap[idxn[j]/bs]-1; 576 #endif 577 if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 578 else { 579 col = data + idxn[j]%bs; 580 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 581 } 582 } 583 } 584 } else { 585 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 586 } 587 } 588 PetscFunctionReturn(0); 589 } 590 591 #undef __FUNCT__ 592 #define __FUNCT__ "MatNorm_MPISBAIJ" 593 PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm) 594 { 595 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 596 PetscErrorCode ierr; 597 PetscReal sum[2],*lnorm2; 598 599 PetscFunctionBegin; 600 if (baij->size == 1) { 601 ierr = MatNorm(baij->A,type,norm);CHKERRQ(ierr); 602 } else { 603 if (type == NORM_FROBENIUS) { 604 ierr = PetscMalloc(2*sizeof(PetscReal),&lnorm2);CHKERRQ(ierr); 605 ierr = MatNorm(baij->A,type,lnorm2);CHKERRQ(ierr); 606 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++; /* squar power of norm(A) */ 607 ierr = MatNorm(baij->B,type,lnorm2);CHKERRQ(ierr); 608 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--; /* squar power of norm(B) */ 609 ierr = MPI_Allreduce(lnorm2,&sum,2,MPIU_REAL,MPI_SUM,mat->comm);CHKERRQ(ierr); 610 *norm = sqrt(sum[0] + 2*sum[1]); 611 ierr = PetscFree(lnorm2);CHKERRQ(ierr); 612 } else { 613 SETERRQ(PETSC_ERR_SUP,"No support for this norm yet"); 614 } 615 } 616 PetscFunctionReturn(0); 617 } 618 619 /* 620 Creates the hash table, and sets the table 621 This table is created only once. 622 If new entried need to be added to the matrix 623 then the hash table has to be destroyed and 624 recreated. 625 */ 626 #undef __FUNCT__ 627 #define __FUNCT__ "MatCreateHashTable_MPISBAIJ_Private" 628 PetscErrorCode MatCreateHashTable_MPISBAIJ_Private(Mat mat,PetscReal factor) 629 { 630 PetscFunctionBegin; 631 SETERRQ(PETSC_ERR_SUP,"Function not yet written for SBAIJ format"); 632 /* PetscFunctionReturn(0); */ 633 } 634 635 #undef __FUNCT__ 636 #define __FUNCT__ "MatAssemblyBegin_MPISBAIJ" 637 PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode) 638 { 639 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 640 PetscErrorCode ierr; 641 PetscInt nstash,reallocs; 642 InsertMode addv; 643 644 PetscFunctionBegin; 645 if (baij->donotstash) { 646 PetscFunctionReturn(0); 647 } 648 649 /* make sure all processors are either in INSERTMODE or ADDMODE */ 650 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,mat->comm);CHKERRQ(ierr); 651 if (addv == (ADD_VALUES|INSERT_VALUES)) { 652 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 653 } 654 mat->insertmode = addv; /* in case this processor had no cache */ 655 656 ierr = MatStashScatterBegin_Private(&mat->stash,baij->rowners_bs);CHKERRQ(ierr); 657 ierr = MatStashScatterBegin_Private(&mat->bstash,baij->rowners);CHKERRQ(ierr); 658 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 659 PetscLogInfo(0,"MatAssemblyBegin_MPISBAIJ:Stash has %D entries,uses %D mallocs.\n",nstash,reallocs); 660 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 661 PetscLogInfo(0,"MatAssemblyBegin_MPISBAIJ:Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs); 662 PetscFunctionReturn(0); 663 } 664 665 #undef __FUNCT__ 666 #define __FUNCT__ "MatAssemblyEnd_MPISBAIJ" 667 PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode) 668 { 669 Mat_MPISBAIJ *baij=(Mat_MPISBAIJ*)mat->data; 670 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)baij->A->data; 671 Mat_SeqBAIJ *b=(Mat_SeqBAIJ*)baij->B->data; 672 PetscErrorCode ierr; 673 PetscInt i,j,rstart,ncols,n,flg,bs2=baij->bs2; 674 PetscInt *row,*col,other_disassembled; 675 PetscTruth r1,r2,r3; 676 MatScalar *val; 677 InsertMode addv = mat->insertmode; 678 679 PetscFunctionBegin; 680 681 if (!baij->donotstash) { 682 while (1) { 683 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 684 if (!flg) break; 685 686 for (i=0; i<n;) { 687 /* Now identify the consecutive vals belonging to the same row */ 688 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 689 if (j < n) ncols = j-i; 690 else ncols = n-i; 691 /* Now assemble all these values with a single function call */ 692 ierr = MatSetValues_MPISBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 693 i = j; 694 } 695 } 696 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 697 /* Now process the block-stash. Since the values are stashed column-oriented, 698 set the roworiented flag to column oriented, and after MatSetValues() 699 restore the original flags */ 700 r1 = baij->roworiented; 701 r2 = a->roworiented; 702 r3 = b->roworiented; 703 baij->roworiented = PETSC_FALSE; 704 a->roworiented = PETSC_FALSE; 705 b->roworiented = PETSC_FALSE; 706 while (1) { 707 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 708 if (!flg) break; 709 710 for (i=0; i<n;) { 711 /* Now identify the consecutive vals belonging to the same row */ 712 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 713 if (j < n) ncols = j-i; 714 else ncols = n-i; 715 ierr = MatSetValuesBlocked_MPISBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 716 i = j; 717 } 718 } 719 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 720 baij->roworiented = r1; 721 a->roworiented = r2; 722 b->roworiented = r3; 723 } 724 725 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 726 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 727 728 /* determine if any processor has disassembled, if so we must 729 also disassemble ourselfs, in order that we may reassemble. */ 730 /* 731 if nonzero structure of submatrix B cannot change then we know that 732 no processor disassembled thus we can skip this stuff 733 */ 734 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 735 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,mat->comm);CHKERRQ(ierr); 736 if (mat->was_assembled && !other_disassembled) { 737 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 738 } 739 } 740 741 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 742 ierr = MatSetUpMultiply_MPISBAIJ(mat);CHKERRQ(ierr); /* setup Mvctx and sMvctx */ 743 } 744 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 745 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 746 747 #if defined(PETSC_USE_BOPT_g) 748 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 749 PetscLogInfo(0,"MatAssemblyEnd_MPISBAIJ:Average Hash Table Search in MatSetValues = %5.2f\n",((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct); 750 baij->ht_total_ct = 0; 751 baij->ht_insert_ct = 0; 752 } 753 #endif 754 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 755 ierr = MatCreateHashTable_MPISBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 756 mat->ops->setvalues = MatSetValues_MPISBAIJ_HT; 757 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPISBAIJ_HT; 758 } 759 760 if (baij->rowvalues) { 761 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 762 baij->rowvalues = 0; 763 } 764 765 PetscFunctionReturn(0); 766 } 767 768 #undef __FUNCT__ 769 #define __FUNCT__ "MatView_MPISBAIJ_ASCIIorDraworSocket" 770 static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 771 { 772 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 773 PetscErrorCode ierr; 774 PetscInt bs = mat->bs; 775 PetscMPIInt size = baij->size,rank = baij->rank; 776 PetscTruth iascii,isdraw; 777 PetscViewer sviewer; 778 PetscViewerFormat format; 779 780 PetscFunctionBegin; 781 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 782 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 783 if (iascii) { 784 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 785 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 786 MatInfo info; 787 ierr = MPI_Comm_rank(mat->comm,&rank);CHKERRQ(ierr); 788 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 789 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n", 790 rank,mat->m,(PetscInt)info.nz_used*bs,(PetscInt)info.nz_allocated*bs, 791 mat->bs,(PetscInt)info.memory);CHKERRQ(ierr); 792 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 793 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 794 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 795 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 796 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 797 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 798 PetscFunctionReturn(0); 799 } else if (format == PETSC_VIEWER_ASCII_INFO) { 800 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 801 PetscFunctionReturn(0); 802 } 803 } 804 805 if (isdraw) { 806 PetscDraw draw; 807 PetscTruth isnull; 808 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 809 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 810 } 811 812 if (size == 1) { 813 ierr = PetscObjectSetName((PetscObject)baij->A,mat->name);CHKERRQ(ierr); 814 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 815 } else { 816 /* assemble the entire matrix onto first processor. */ 817 Mat A; 818 Mat_SeqSBAIJ *Aloc; 819 Mat_SeqBAIJ *Bloc; 820 PetscInt M = mat->M,N = mat->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 821 MatScalar *a; 822 823 /* Should this be the same type as mat? */ 824 if (!rank) { 825 ierr = MatCreate(mat->comm,M,N,M,N,&A);CHKERRQ(ierr); 826 } else { 827 ierr = MatCreate(mat->comm,0,0,M,N,&A);CHKERRQ(ierr); 828 } 829 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 830 ierr = MatMPISBAIJSetPreallocation(A,mat->bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 831 PetscLogObjectParent(mat,A); 832 833 /* copy over the A part */ 834 Aloc = (Mat_SeqSBAIJ*)baij->A->data; 835 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 836 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 837 838 for (i=0; i<mbs; i++) { 839 rvals[0] = bs*(baij->rstart + i); 840 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 841 for (j=ai[i]; j<ai[i+1]; j++) { 842 col = (baij->cstart+aj[j])*bs; 843 for (k=0; k<bs; k++) { 844 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 845 col++; a += bs; 846 } 847 } 848 } 849 /* copy over the B part */ 850 Bloc = (Mat_SeqBAIJ*)baij->B->data; 851 ai = Bloc->i; aj = Bloc->j; a = Bloc->a; 852 for (i=0; i<mbs; i++) { 853 rvals[0] = bs*(baij->rstart + i); 854 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 855 for (j=ai[i]; j<ai[i+1]; j++) { 856 col = baij->garray[aj[j]]*bs; 857 for (k=0; k<bs; k++) { 858 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 859 col++; a += bs; 860 } 861 } 862 } 863 ierr = PetscFree(rvals);CHKERRQ(ierr); 864 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 865 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 866 /* 867 Everyone has to call to draw the matrix since the graphics waits are 868 synchronized across all processors that share the PetscDraw object 869 */ 870 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 871 if (!rank) { 872 ierr = PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,mat->name);CHKERRQ(ierr); 873 ierr = MatView(((Mat_MPISBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 874 } 875 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 876 ierr = MatDestroy(A);CHKERRQ(ierr); 877 } 878 PetscFunctionReturn(0); 879 } 880 881 #undef __FUNCT__ 882 #define __FUNCT__ "MatView_MPISBAIJ" 883 PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer) 884 { 885 PetscErrorCode ierr; 886 PetscTruth iascii,isdraw,issocket,isbinary; 887 888 PetscFunctionBegin; 889 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 890 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 891 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 892 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 893 if (iascii || isdraw || issocket || isbinary) { 894 ierr = MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 895 } else { 896 SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPISBAIJ matrices",((PetscObject)viewer)->type_name); 897 } 898 PetscFunctionReturn(0); 899 } 900 901 #undef __FUNCT__ 902 #define __FUNCT__ "MatDestroy_MPISBAIJ" 903 PetscErrorCode MatDestroy_MPISBAIJ(Mat mat) 904 { 905 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 906 PetscErrorCode ierr; 907 908 PetscFunctionBegin; 909 #if defined(PETSC_USE_LOG) 910 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->M,mat->N); 911 #endif 912 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 913 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 914 ierr = PetscFree(baij->rowners);CHKERRQ(ierr); 915 ierr = MatDestroy(baij->A);CHKERRQ(ierr); 916 ierr = MatDestroy(baij->B);CHKERRQ(ierr); 917 #if defined (PETSC_USE_CTABLE) 918 if (baij->colmap) {ierr = PetscTableDelete(baij->colmap);CHKERRQ(ierr);} 919 #else 920 if (baij->colmap) {ierr = PetscFree(baij->colmap);CHKERRQ(ierr);} 921 #endif 922 if (baij->garray) {ierr = PetscFree(baij->garray);CHKERRQ(ierr);} 923 if (baij->lvec) {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);} 924 if (baij->Mvctx) {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);} 925 if (baij->slvec0) { 926 ierr = VecDestroy(baij->slvec0);CHKERRQ(ierr); 927 ierr = VecDestroy(baij->slvec0b);CHKERRQ(ierr); 928 } 929 if (baij->slvec1) { 930 ierr = VecDestroy(baij->slvec1);CHKERRQ(ierr); 931 ierr = VecDestroy(baij->slvec1a);CHKERRQ(ierr); 932 ierr = VecDestroy(baij->slvec1b);CHKERRQ(ierr); 933 } 934 if (baij->sMvctx) {ierr = VecScatterDestroy(baij->sMvctx);CHKERRQ(ierr);} 935 if (baij->rowvalues) {ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr);} 936 if (baij->barray) {ierr = PetscFree(baij->barray);CHKERRQ(ierr);} 937 if (baij->hd) {ierr = PetscFree(baij->hd);CHKERRQ(ierr);} 938 #if defined(PETSC_USE_MAT_SINGLE) 939 if (baij->setvaluescopy) {ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr);} 940 #endif 941 ierr = PetscFree(baij);CHKERRQ(ierr); 942 943 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 944 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 945 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);CHKERRQ(ierr); 946 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 947 PetscFunctionReturn(0); 948 } 949 950 #undef __FUNCT__ 951 #define __FUNCT__ "MatMult_MPISBAIJ" 952 PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy) 953 { 954 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 955 PetscErrorCode ierr; 956 PetscInt nt,mbs=a->mbs,bs=A->bs; 957 PetscScalar *x,*from,zero=0.0; 958 959 PetscFunctionBegin; 960 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 961 if (nt != A->n) { 962 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 963 } 964 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 965 if (nt != A->m) { 966 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 967 } 968 969 /* diagonal part */ 970 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 971 ierr = VecSet(&zero,a->slvec1b);CHKERRQ(ierr); 972 973 /* subdiagonal part */ 974 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 975 976 /* copy x into the vec slvec0 */ 977 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 978 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 979 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 980 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 981 982 ierr = VecScatterBegin(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 983 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 984 ierr = VecScatterEnd(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 985 986 /* supperdiagonal part */ 987 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 988 989 PetscFunctionReturn(0); 990 } 991 992 #undef __FUNCT__ 993 #define __FUNCT__ "MatMult_MPISBAIJ_2comm" 994 PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy) 995 { 996 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 997 PetscErrorCode ierr; 998 PetscInt nt; 999 1000 PetscFunctionBegin; 1001 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1002 if (nt != A->n) { 1003 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1004 } 1005 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1006 if (nt != A->m) { 1007 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1008 } 1009 1010 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1011 /* do diagonal part */ 1012 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1013 /* do supperdiagonal part */ 1014 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1015 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1016 /* do subdiagonal part */ 1017 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1018 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1019 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1020 1021 PetscFunctionReturn(0); 1022 } 1023 1024 #undef __FUNCT__ 1025 #define __FUNCT__ "MatMultAdd_MPISBAIJ" 1026 PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1027 { 1028 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1029 PetscErrorCode ierr; 1030 PetscInt mbs=a->mbs,bs=A->bs; 1031 PetscScalar *x,*from,zero=0.0; 1032 1033 PetscFunctionBegin; 1034 /* 1035 PetscSynchronizedPrintf(A->comm," MatMultAdd is called ...\n"); 1036 PetscSynchronizedFlush(A->comm); 1037 */ 1038 /* diagonal part */ 1039 ierr = (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);CHKERRQ(ierr); 1040 ierr = VecSet(&zero,a->slvec1b);CHKERRQ(ierr); 1041 1042 /* subdiagonal part */ 1043 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 1044 1045 /* copy x into the vec slvec0 */ 1046 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 1047 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1048 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 1049 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 1050 1051 ierr = VecScatterBegin(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 1052 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1053 ierr = VecScatterEnd(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 1054 1055 /* supperdiagonal part */ 1056 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);CHKERRQ(ierr); 1057 1058 PetscFunctionReturn(0); 1059 } 1060 1061 #undef __FUNCT__ 1062 #define __FUNCT__ "MatMultAdd_MPISBAIJ_2comm" 1063 PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz) 1064 { 1065 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1066 PetscErrorCode ierr; 1067 1068 PetscFunctionBegin; 1069 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1070 /* do diagonal part */ 1071 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1072 /* do supperdiagonal part */ 1073 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1074 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1075 1076 /* do subdiagonal part */ 1077 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1078 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1079 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1080 1081 PetscFunctionReturn(0); 1082 } 1083 1084 #undef __FUNCT__ 1085 #define __FUNCT__ "MatMultTranspose_MPISBAIJ" 1086 PetscErrorCode MatMultTranspose_MPISBAIJ(Mat A,Vec xx,Vec yy) 1087 { 1088 PetscErrorCode ierr; 1089 1090 PetscFunctionBegin; 1091 ierr = MatMult(A,xx,yy);CHKERRQ(ierr); 1092 PetscFunctionReturn(0); 1093 } 1094 1095 #undef __FUNCT__ 1096 #define __FUNCT__ "MatMultTransposeAdd_MPISBAIJ" 1097 PetscErrorCode MatMultTransposeAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1098 { 1099 PetscErrorCode ierr; 1100 1101 PetscFunctionBegin; 1102 ierr = MatMultAdd(A,xx,yy,zz);CHKERRQ(ierr); 1103 PetscFunctionReturn(0); 1104 } 1105 1106 /* 1107 This only works correctly for square matrices where the subblock A->A is the 1108 diagonal block 1109 */ 1110 #undef __FUNCT__ 1111 #define __FUNCT__ "MatGetDiagonal_MPISBAIJ" 1112 PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v) 1113 { 1114 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1115 PetscErrorCode ierr; 1116 1117 PetscFunctionBegin; 1118 /* if (a->M != a->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 1119 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1120 PetscFunctionReturn(0); 1121 } 1122 1123 #undef __FUNCT__ 1124 #define __FUNCT__ "MatScale_MPISBAIJ" 1125 PetscErrorCode MatScale_MPISBAIJ(const PetscScalar *aa,Mat A) 1126 { 1127 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1128 PetscErrorCode ierr; 1129 1130 PetscFunctionBegin; 1131 ierr = MatScale(aa,a->A);CHKERRQ(ierr); 1132 ierr = MatScale(aa,a->B);CHKERRQ(ierr); 1133 PetscFunctionReturn(0); 1134 } 1135 1136 #undef __FUNCT__ 1137 #define __FUNCT__ "MatGetRow_MPISBAIJ" 1138 PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1139 { 1140 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 1141 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1142 PetscErrorCode ierr; 1143 PetscInt bs = matin->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1144 PetscInt nztot,nzA,nzB,lrow,brstart = mat->rstart*bs,brend = mat->rend*bs; 1145 PetscInt *cmap,*idx_p,cstart = mat->cstart; 1146 1147 PetscFunctionBegin; 1148 if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1149 mat->getrowactive = PETSC_TRUE; 1150 1151 if (!mat->rowvalues && (idx || v)) { 1152 /* 1153 allocate enough space to hold information from the longest row. 1154 */ 1155 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 1156 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 1157 PetscInt max = 1,mbs = mat->mbs,tmp; 1158 for (i=0; i<mbs; i++) { 1159 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 1160 if (max < tmp) { max = tmp; } 1161 } 1162 ierr = PetscMalloc(max*bs2*(sizeof(PetscInt)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1163 mat->rowindices = (PetscInt*)(mat->rowvalues + max*bs2); 1164 } 1165 1166 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 1167 lrow = row - brstart; /* local row index */ 1168 1169 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1170 if (!v) {pvA = 0; pvB = 0;} 1171 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1172 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1173 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1174 nztot = nzA + nzB; 1175 1176 cmap = mat->garray; 1177 if (v || idx) { 1178 if (nztot) { 1179 /* Sort by increasing column numbers, assuming A and B already sorted */ 1180 PetscInt imark = -1; 1181 if (v) { 1182 *v = v_p = mat->rowvalues; 1183 for (i=0; i<nzB; i++) { 1184 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1185 else break; 1186 } 1187 imark = i; 1188 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1189 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1190 } 1191 if (idx) { 1192 *idx = idx_p = mat->rowindices; 1193 if (imark > -1) { 1194 for (i=0; i<imark; i++) { 1195 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1196 } 1197 } else { 1198 for (i=0; i<nzB; i++) { 1199 if (cmap[cworkB[i]/bs] < cstart) 1200 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1201 else break; 1202 } 1203 imark = i; 1204 } 1205 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1206 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1207 } 1208 } else { 1209 if (idx) *idx = 0; 1210 if (v) *v = 0; 1211 } 1212 } 1213 *nz = nztot; 1214 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1215 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1216 PetscFunctionReturn(0); 1217 } 1218 1219 #undef __FUNCT__ 1220 #define __FUNCT__ "MatRestoreRow_MPISBAIJ" 1221 PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1222 { 1223 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1224 1225 PetscFunctionBegin; 1226 if (baij->getrowactive == PETSC_FALSE) { 1227 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1228 } 1229 baij->getrowactive = PETSC_FALSE; 1230 PetscFunctionReturn(0); 1231 } 1232 1233 #undef __FUNCT__ 1234 #define __FUNCT__ "MatZeroEntries_MPISBAIJ" 1235 PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A) 1236 { 1237 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1238 PetscErrorCode ierr; 1239 1240 PetscFunctionBegin; 1241 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1242 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1243 PetscFunctionReturn(0); 1244 } 1245 1246 #undef __FUNCT__ 1247 #define __FUNCT__ "MatGetInfo_MPISBAIJ" 1248 PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1249 { 1250 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1251 Mat A = a->A,B = a->B; 1252 PetscErrorCode ierr; 1253 PetscReal isend[5],irecv[5]; 1254 1255 PetscFunctionBegin; 1256 info->block_size = (PetscReal)matin->bs; 1257 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1258 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1259 isend[3] = info->memory; isend[4] = info->mallocs; 1260 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1261 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1262 isend[3] += info->memory; isend[4] += info->mallocs; 1263 if (flag == MAT_LOCAL) { 1264 info->nz_used = isend[0]; 1265 info->nz_allocated = isend[1]; 1266 info->nz_unneeded = isend[2]; 1267 info->memory = isend[3]; 1268 info->mallocs = isend[4]; 1269 } else if (flag == MAT_GLOBAL_MAX) { 1270 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,matin->comm);CHKERRQ(ierr); 1271 info->nz_used = irecv[0]; 1272 info->nz_allocated = irecv[1]; 1273 info->nz_unneeded = irecv[2]; 1274 info->memory = irecv[3]; 1275 info->mallocs = irecv[4]; 1276 } else if (flag == MAT_GLOBAL_SUM) { 1277 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,matin->comm);CHKERRQ(ierr); 1278 info->nz_used = irecv[0]; 1279 info->nz_allocated = irecv[1]; 1280 info->nz_unneeded = irecv[2]; 1281 info->memory = irecv[3]; 1282 info->mallocs = irecv[4]; 1283 } else { 1284 SETERRQ1(PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1285 } 1286 info->rows_global = (PetscReal)A->M; 1287 info->columns_global = (PetscReal)A->N; 1288 info->rows_local = (PetscReal)A->m; 1289 info->columns_local = (PetscReal)A->N; 1290 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1291 info->fill_ratio_needed = 0; 1292 info->factor_mallocs = 0; 1293 PetscFunctionReturn(0); 1294 } 1295 1296 #undef __FUNCT__ 1297 #define __FUNCT__ "MatSetOption_MPISBAIJ" 1298 PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op) 1299 { 1300 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1301 PetscErrorCode ierr; 1302 1303 PetscFunctionBegin; 1304 switch (op) { 1305 case MAT_NO_NEW_NONZERO_LOCATIONS: 1306 case MAT_YES_NEW_NONZERO_LOCATIONS: 1307 case MAT_COLUMNS_UNSORTED: 1308 case MAT_COLUMNS_SORTED: 1309 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1310 case MAT_KEEP_ZEROED_ROWS: 1311 case MAT_NEW_NONZERO_LOCATION_ERR: 1312 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1313 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1314 break; 1315 case MAT_ROW_ORIENTED: 1316 a->roworiented = PETSC_TRUE; 1317 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1318 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1319 break; 1320 case MAT_ROWS_SORTED: 1321 case MAT_ROWS_UNSORTED: 1322 case MAT_YES_NEW_DIAGONALS: 1323 PetscLogInfo(A,"Info:MatSetOption_MPIBAIJ:Option ignored\n"); 1324 break; 1325 case MAT_COLUMN_ORIENTED: 1326 a->roworiented = PETSC_FALSE; 1327 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1328 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1329 break; 1330 case MAT_IGNORE_OFF_PROC_ENTRIES: 1331 a->donotstash = PETSC_TRUE; 1332 break; 1333 case MAT_NO_NEW_DIAGONALS: 1334 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 1335 case MAT_USE_HASH_TABLE: 1336 a->ht_flag = PETSC_TRUE; 1337 break; 1338 case MAT_NOT_SYMMETRIC: 1339 case MAT_NOT_STRUCTURALLY_SYMMETRIC: 1340 case MAT_HERMITIAN: 1341 SETERRQ(PETSC_ERR_SUP,"Matrix must be symmetric"); 1342 case MAT_SYMMETRIC: 1343 case MAT_STRUCTURALLY_SYMMETRIC: 1344 case MAT_NOT_HERMITIAN: 1345 case MAT_SYMMETRY_ETERNAL: 1346 case MAT_NOT_SYMMETRY_ETERNAL: 1347 break; 1348 default: 1349 SETERRQ(PETSC_ERR_SUP,"unknown option"); 1350 } 1351 PetscFunctionReturn(0); 1352 } 1353 1354 #undef __FUNCT__ 1355 #define __FUNCT__ "MatTranspose_MPISBAIJ" 1356 PetscErrorCode MatTranspose_MPISBAIJ(Mat A,Mat *B) 1357 { 1358 PetscErrorCode ierr; 1359 PetscFunctionBegin; 1360 ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr); 1361 PetscFunctionReturn(0); 1362 } 1363 1364 #undef __FUNCT__ 1365 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ" 1366 PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1367 { 1368 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1369 Mat a = baij->A,b = baij->B; 1370 PetscErrorCode ierr; 1371 PetscInt s1,s2,s3; 1372 1373 PetscFunctionBegin; 1374 if (ll != rr) { 1375 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1376 } 1377 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1378 if (rr) { 1379 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1380 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1381 /* Overlap communication with computation. */ 1382 ierr = VecScatterBegin(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1383 /*} if (ll) { */ 1384 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1385 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1386 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1387 /* } */ 1388 /* scale the diagonal block */ 1389 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1390 1391 /* if (rr) { */ 1392 /* Do a scatter end and then right scale the off-diagonal block */ 1393 ierr = VecScatterEnd(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1394 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1395 } 1396 1397 PetscFunctionReturn(0); 1398 } 1399 1400 #undef __FUNCT__ 1401 #define __FUNCT__ "MatZeroRows_MPISBAIJ" 1402 PetscErrorCode MatZeroRows_MPISBAIJ(Mat A,IS is,const PetscScalar *diag) 1403 { 1404 PetscFunctionBegin; 1405 SETERRQ(PETSC_ERR_SUP,"No support for this function yet"); 1406 } 1407 1408 #undef __FUNCT__ 1409 #define __FUNCT__ "MatPrintHelp_MPISBAIJ" 1410 PetscErrorCode MatPrintHelp_MPISBAIJ(Mat A) 1411 { 1412 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1413 MPI_Comm comm = A->comm; 1414 static PetscTruth called = PETSC_FALSE; 1415 PetscErrorCode ierr; 1416 1417 PetscFunctionBegin; 1418 if (!a->rank) { 1419 ierr = MatPrintHelp_SeqSBAIJ(a->A);CHKERRQ(ierr); 1420 } 1421 if (called) {PetscFunctionReturn(0);} else called = PETSC_TRUE; 1422 ierr = (*PetscHelpPrintf)(comm," Options for MATMPISBAIJ matrix format (the defaults):\n");CHKERRQ(ierr); 1423 ierr = (*PetscHelpPrintf)(comm," -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n");CHKERRQ(ierr); 1424 PetscFunctionReturn(0); 1425 } 1426 1427 #undef __FUNCT__ 1428 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1429 PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A) 1430 { 1431 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1432 PetscErrorCode ierr; 1433 1434 PetscFunctionBegin; 1435 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1436 PetscFunctionReturn(0); 1437 } 1438 1439 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat *); 1440 1441 #undef __FUNCT__ 1442 #define __FUNCT__ "MatEqual_MPISBAIJ" 1443 PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscTruth *flag) 1444 { 1445 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1446 Mat a,b,c,d; 1447 PetscTruth flg; 1448 PetscErrorCode ierr; 1449 1450 PetscFunctionBegin; 1451 a = matA->A; b = matA->B; 1452 c = matB->A; d = matB->B; 1453 1454 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1455 if (flg == PETSC_TRUE) { 1456 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1457 } 1458 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1459 PetscFunctionReturn(0); 1460 } 1461 1462 #undef __FUNCT__ 1463 #define __FUNCT__ "MatSetUpPreallocation_MPISBAIJ" 1464 PetscErrorCode MatSetUpPreallocation_MPISBAIJ(Mat A) 1465 { 1466 PetscErrorCode ierr; 1467 1468 PetscFunctionBegin; 1469 ierr = MatMPISBAIJSetPreallocation(A,1,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1470 PetscFunctionReturn(0); 1471 } 1472 1473 #undef __FUNCT__ 1474 #define __FUNCT__ "MatGetSubMatrices_MPISBAIJ" 1475 PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1476 { 1477 PetscErrorCode ierr; 1478 PetscInt i; 1479 PetscTruth flg; 1480 1481 PetscFunctionBegin; 1482 for (i=0; i<n; i++) { 1483 ierr = ISEqual(irow[i],icol[i],&flg);CHKERRQ(ierr); 1484 if (!flg) { 1485 SETERRQ(PETSC_ERR_SUP,"Can only get symmetric submatrix for MPISBAIJ matrices"); 1486 } 1487 } 1488 ierr = MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B);CHKERRQ(ierr); 1489 PetscFunctionReturn(0); 1490 } 1491 1492 1493 /* -------------------------------------------------------------------*/ 1494 static struct _MatOps MatOps_Values = { 1495 MatSetValues_MPISBAIJ, 1496 MatGetRow_MPISBAIJ, 1497 MatRestoreRow_MPISBAIJ, 1498 MatMult_MPISBAIJ, 1499 /* 4*/ MatMultAdd_MPISBAIJ, 1500 MatMultTranspose_MPISBAIJ, 1501 MatMultTransposeAdd_MPISBAIJ, 1502 0, 1503 0, 1504 0, 1505 /*10*/ 0, 1506 0, 1507 0, 1508 MatRelax_MPISBAIJ, 1509 MatTranspose_MPISBAIJ, 1510 /*15*/ MatGetInfo_MPISBAIJ, 1511 MatEqual_MPISBAIJ, 1512 MatGetDiagonal_MPISBAIJ, 1513 MatDiagonalScale_MPISBAIJ, 1514 MatNorm_MPISBAIJ, 1515 /*20*/ MatAssemblyBegin_MPISBAIJ, 1516 MatAssemblyEnd_MPISBAIJ, 1517 0, 1518 MatSetOption_MPISBAIJ, 1519 MatZeroEntries_MPISBAIJ, 1520 /*25*/ MatZeroRows_MPISBAIJ, 1521 0, 1522 0, 1523 0, 1524 0, 1525 /*30*/ MatSetUpPreallocation_MPISBAIJ, 1526 0, 1527 0, 1528 0, 1529 0, 1530 /*35*/ MatDuplicate_MPISBAIJ, 1531 0, 1532 0, 1533 0, 1534 0, 1535 /*40*/ 0, 1536 MatGetSubMatrices_MPISBAIJ, 1537 MatIncreaseOverlap_MPISBAIJ, 1538 MatGetValues_MPISBAIJ, 1539 0, 1540 /*45*/ MatPrintHelp_MPISBAIJ, 1541 MatScale_MPISBAIJ, 1542 0, 1543 0, 1544 0, 1545 /*50*/ 0, 1546 0, 1547 0, 1548 0, 1549 0, 1550 /*55*/ 0, 1551 0, 1552 MatSetUnfactored_MPISBAIJ, 1553 0, 1554 MatSetValuesBlocked_MPISBAIJ, 1555 /*60*/ 0, 1556 0, 1557 0, 1558 MatGetPetscMaps_Petsc, 1559 0, 1560 /*65*/ 0, 1561 0, 1562 0, 1563 0, 1564 0, 1565 /*70*/ MatGetRowMax_MPISBAIJ, 1566 0, 1567 0, 1568 0, 1569 0, 1570 /*75*/ 0, 1571 0, 1572 0, 1573 0, 1574 0, 1575 /*80*/ 0, 1576 0, 1577 0, 1578 0, 1579 MatLoad_MPISBAIJ, 1580 /*85*/ 0, 1581 0, 1582 0, 1583 0, 1584 0, 1585 /*90*/ 0, 1586 0, 1587 0, 1588 0, 1589 0, 1590 /*95*/ 0, 1591 0, 1592 0, 1593 0}; 1594 1595 1596 EXTERN_C_BEGIN 1597 #undef __FUNCT__ 1598 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1599 PetscErrorCode MatGetDiagonalBlock_MPISBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1600 { 1601 PetscFunctionBegin; 1602 *a = ((Mat_MPISBAIJ *)A->data)->A; 1603 *iscopy = PETSC_FALSE; 1604 PetscFunctionReturn(0); 1605 } 1606 EXTERN_C_END 1607 1608 EXTERN_C_BEGIN 1609 #undef __FUNCT__ 1610 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ" 1611 PetscErrorCode MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 1612 { 1613 Mat_MPISBAIJ *b; 1614 PetscErrorCode ierr; 1615 PetscInt i,mbs,Mbs; 1616 1617 PetscFunctionBegin; 1618 ierr = PetscOptionsGetInt(B->prefix,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1619 1620 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 1621 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1622 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1623 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 1624 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 1625 if (d_nnz) { 1626 for (i=0; i<B->m/bs; i++) { 1627 if (d_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than -1: local row %D value %D",i,d_nnz[i]); 1628 } 1629 } 1630 if (o_nnz) { 1631 for (i=0; i<B->m/bs; i++) { 1632 if (o_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than -1: local row %D value %D",i,o_nnz[i]); 1633 } 1634 } 1635 B->preallocated = PETSC_TRUE; 1636 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->m,&B->M);CHKERRQ(ierr); 1637 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->n,&B->N);CHKERRQ(ierr); 1638 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1639 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->cmap);CHKERRQ(ierr); 1640 1641 b = (Mat_MPISBAIJ*)B->data; 1642 mbs = B->m/bs; 1643 Mbs = B->M/bs; 1644 if (mbs*bs != B->m) { 1645 SETERRQ2(PETSC_ERR_ARG_SIZ,"No of local rows %D must be divisible by blocksize %D",B->m,bs); 1646 } 1647 1648 B->bs = bs; 1649 b->bs2 = bs*bs; 1650 b->mbs = mbs; 1651 b->nbs = mbs; 1652 b->Mbs = Mbs; 1653 b->Nbs = Mbs; 1654 1655 ierr = MPI_Allgather(&b->mbs,1,MPI_INT,b->rowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 1656 b->rowners[0] = 0; 1657 for (i=2; i<=b->size; i++) { 1658 b->rowners[i] += b->rowners[i-1]; 1659 } 1660 b->rstart = b->rowners[b->rank]; 1661 b->rend = b->rowners[b->rank+1]; 1662 b->cstart = b->rstart; 1663 b->cend = b->rend; 1664 for (i=0; i<=b->size; i++) { 1665 b->rowners_bs[i] = b->rowners[i]*bs; 1666 } 1667 b->rstart_bs = b-> rstart*bs; 1668 b->rend_bs = b->rend*bs; 1669 1670 b->cstart_bs = b->cstart*bs; 1671 b->cend_bs = b->cend*bs; 1672 1673 ierr = MatCreate(PETSC_COMM_SELF,B->m,B->m,B->m,B->m,&b->A);CHKERRQ(ierr); 1674 ierr = MatSetType(b->A,MATSEQSBAIJ);CHKERRQ(ierr); 1675 ierr = MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1676 PetscLogObjectParent(B,b->A); 1677 1678 ierr = MatCreate(PETSC_COMM_SELF,B->m,B->M,B->m,B->M,&b->B);CHKERRQ(ierr); 1679 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 1680 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 1681 PetscLogObjectParent(B,b->B); 1682 1683 /* build cache for off array entries formed */ 1684 ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr); 1685 1686 PetscFunctionReturn(0); 1687 } 1688 EXTERN_C_END 1689 1690 /*MC 1691 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 1692 based on block compressed sparse row format. Only the upper triangular portion of the matrix is stored. 1693 1694 Options Database Keys: 1695 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions() 1696 1697 Level: beginner 1698 1699 .seealso: MatCreateMPISBAIJ 1700 M*/ 1701 1702 EXTERN_C_BEGIN 1703 #undef __FUNCT__ 1704 #define __FUNCT__ "MatCreate_MPISBAIJ" 1705 PetscErrorCode MatCreate_MPISBAIJ(Mat B) 1706 { 1707 Mat_MPISBAIJ *b; 1708 PetscErrorCode ierr; 1709 PetscTruth flg; 1710 1711 PetscFunctionBegin; 1712 1713 ierr = PetscNew(Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1714 B->data = (void*)b; 1715 ierr = PetscMemzero(b,sizeof(Mat_MPISBAIJ));CHKERRQ(ierr); 1716 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1717 1718 B->ops->destroy = MatDestroy_MPISBAIJ; 1719 B->ops->view = MatView_MPISBAIJ; 1720 B->mapping = 0; 1721 B->factor = 0; 1722 B->assembled = PETSC_FALSE; 1723 1724 B->insertmode = NOT_SET_VALUES; 1725 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1726 ierr = MPI_Comm_size(B->comm,&b->size);CHKERRQ(ierr); 1727 1728 /* build local table of row and column ownerships */ 1729 ierr = PetscMalloc(3*(b->size+2)*sizeof(PetscInt),&b->rowners);CHKERRQ(ierr); 1730 b->cowners = b->rowners + b->size + 2; 1731 b->rowners_bs = b->cowners + b->size + 2; 1732 PetscLogObjectMemory(B,3*(b->size+2)*sizeof(PetscInt)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1733 1734 /* build cache for off array entries formed */ 1735 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 1736 b->donotstash = PETSC_FALSE; 1737 b->colmap = PETSC_NULL; 1738 b->garray = PETSC_NULL; 1739 b->roworiented = PETSC_TRUE; 1740 1741 #if defined(PETSC_USE_MAT_SINGLE) 1742 /* stuff for MatSetValues_XXX in single precision */ 1743 b->setvalueslen = 0; 1744 b->setvaluescopy = PETSC_NULL; 1745 #endif 1746 1747 /* stuff used in block assembly */ 1748 b->barray = 0; 1749 1750 /* stuff used for matrix vector multiply */ 1751 b->lvec = 0; 1752 b->Mvctx = 0; 1753 b->slvec0 = 0; 1754 b->slvec0b = 0; 1755 b->slvec1 = 0; 1756 b->slvec1a = 0; 1757 b->slvec1b = 0; 1758 b->sMvctx = 0; 1759 1760 /* stuff for MatGetRow() */ 1761 b->rowindices = 0; 1762 b->rowvalues = 0; 1763 b->getrowactive = PETSC_FALSE; 1764 1765 /* hash table stuff */ 1766 b->ht = 0; 1767 b->hd = 0; 1768 b->ht_size = 0; 1769 b->ht_flag = PETSC_FALSE; 1770 b->ht_fact = 0; 1771 b->ht_total_ct = 0; 1772 b->ht_insert_ct = 0; 1773 1774 ierr = PetscOptionsHasName(B->prefix,"-mat_use_hash_table",&flg);CHKERRQ(ierr); 1775 if (flg) { 1776 PetscReal fact = 1.39; 1777 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 1778 ierr = PetscOptionsGetReal(B->prefix,"-mat_use_hash_table",&fact,PETSC_NULL);CHKERRQ(ierr); 1779 if (fact <= 1.0) fact = 1.39; 1780 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1781 PetscLogInfo(0,"MatCreateMPISBAIJ:Hash table Factor used %5.2f\n",fact); 1782 } 1783 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1784 "MatStoreValues_MPISBAIJ", 1785 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1786 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1787 "MatRetrieveValues_MPISBAIJ", 1788 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1789 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1790 "MatGetDiagonalBlock_MPISBAIJ", 1791 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1792 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPISBAIJSetPreallocation_C", 1793 "MatMPISBAIJSetPreallocation_MPISBAIJ", 1794 MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr); 1795 B->symmetric = PETSC_TRUE; 1796 B->structurally_symmetric = PETSC_TRUE; 1797 B->symmetric_set = PETSC_TRUE; 1798 B->structurally_symmetric_set = PETSC_TRUE; 1799 PetscFunctionReturn(0); 1800 } 1801 EXTERN_C_END 1802 1803 /*MC 1804 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 1805 1806 This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator, 1807 and MATMPISBAIJ otherwise. 1808 1809 Options Database Keys: 1810 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions() 1811 1812 Level: beginner 1813 1814 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ 1815 M*/ 1816 1817 EXTERN_C_BEGIN 1818 #undef __FUNCT__ 1819 #define __FUNCT__ "MatCreate_SBAIJ" 1820 PetscErrorCode MatCreate_SBAIJ(Mat A) 1821 { 1822 PetscErrorCode ierr; 1823 PetscMPIInt size; 1824 1825 PetscFunctionBegin; 1826 ierr = PetscObjectChangeTypeName((PetscObject)A,MATSBAIJ);CHKERRQ(ierr); 1827 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 1828 if (size == 1) { 1829 ierr = MatSetType(A,MATSEQSBAIJ);CHKERRQ(ierr); 1830 } else { 1831 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 1832 } 1833 PetscFunctionReturn(0); 1834 } 1835 EXTERN_C_END 1836 1837 #undef __FUNCT__ 1838 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1839 /*@C 1840 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1841 the user should preallocate the matrix storage by setting the parameters 1842 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1843 performance can be increased by more than a factor of 50. 1844 1845 Collective on Mat 1846 1847 Input Parameters: 1848 + A - the matrix 1849 . bs - size of blockk 1850 . d_nz - number of block nonzeros per block row in diagonal portion of local 1851 submatrix (same for all local rows) 1852 . d_nnz - array containing the number of block nonzeros in the various block rows 1853 in the upper triangular and diagonal part of the in diagonal portion of the local 1854 (possibly different for each block row) or PETSC_NULL. You must leave room 1855 for the diagonal entry even if it is zero. 1856 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1857 submatrix (same for all local rows). 1858 - o_nnz - array containing the number of nonzeros in the various block rows of the 1859 off-diagonal portion of the local submatrix (possibly different for 1860 each block row) or PETSC_NULL. 1861 1862 1863 Options Database Keys: 1864 . -mat_no_unroll - uses code that does not unroll the loops in the 1865 block calculations (much slower) 1866 . -mat_block_size - size of the blocks to use 1867 1868 Notes: 1869 1870 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1871 than it must be used on all processors that share the object for that argument. 1872 1873 Storage Information: 1874 For a square global matrix we define each processor's diagonal portion 1875 to be its local rows and the corresponding columns (a square submatrix); 1876 each processor's off-diagonal portion encompasses the remainder of the 1877 local matrix (a rectangular submatrix). 1878 1879 The user can specify preallocated storage for the diagonal part of 1880 the local submatrix with either d_nz or d_nnz (not both). Set 1881 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1882 memory allocation. Likewise, specify preallocated storage for the 1883 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1884 1885 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1886 the figure below we depict these three local rows and all columns (0-11). 1887 1888 .vb 1889 0 1 2 3 4 5 6 7 8 9 10 11 1890 ------------------- 1891 row 3 | o o o d d d o o o o o o 1892 row 4 | o o o d d d o o o o o o 1893 row 5 | o o o d d d o o o o o o 1894 ------------------- 1895 .ve 1896 1897 Thus, any entries in the d locations are stored in the d (diagonal) 1898 submatrix, and any entries in the o locations are stored in the 1899 o (off-diagonal) submatrix. Note that the d matrix is stored in 1900 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1901 1902 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1903 plus the diagonal part of the d matrix, 1904 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1905 In general, for PDE problems in which most nonzeros are near the diagonal, 1906 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1907 or you will get TERRIBLE performance; see the users' manual chapter on 1908 matrices. 1909 1910 Level: intermediate 1911 1912 .keywords: matrix, block, aij, compressed row, sparse, parallel 1913 1914 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1915 @*/ 1916 PetscErrorCode MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 1917 { 1918 PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 1919 1920 PetscFunctionBegin; 1921 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 1922 if (f) { 1923 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1924 } 1925 PetscFunctionReturn(0); 1926 } 1927 1928 #undef __FUNCT__ 1929 #define __FUNCT__ "MatCreateMPISBAIJ" 1930 /*@C 1931 MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1932 (block compressed row). For good matrix assembly performance 1933 the user should preallocate the matrix storage by setting the parameters 1934 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1935 performance can be increased by more than a factor of 50. 1936 1937 Collective on MPI_Comm 1938 1939 Input Parameters: 1940 + comm - MPI communicator 1941 . bs - size of blockk 1942 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1943 This value should be the same as the local size used in creating the 1944 y vector for the matrix-vector product y = Ax. 1945 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1946 This value should be the same as the local size used in creating the 1947 x vector for the matrix-vector product y = Ax. 1948 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1949 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1950 . d_nz - number of block nonzeros per block row in diagonal portion of local 1951 submatrix (same for all local rows) 1952 . d_nnz - array containing the number of block nonzeros in the various block rows 1953 in the upper triangular portion of the in diagonal portion of the local 1954 (possibly different for each block block row) or PETSC_NULL. 1955 You must leave room for the diagonal entry even if it is zero. 1956 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1957 submatrix (same for all local rows). 1958 - o_nnz - array containing the number of nonzeros in the various block rows of the 1959 off-diagonal portion of the local submatrix (possibly different for 1960 each block row) or PETSC_NULL. 1961 1962 Output Parameter: 1963 . A - the matrix 1964 1965 Options Database Keys: 1966 . -mat_no_unroll - uses code that does not unroll the loops in the 1967 block calculations (much slower) 1968 . -mat_block_size - size of the blocks to use 1969 . -mat_mpi - use the parallel matrix data structures even on one processor 1970 (defaults to using SeqBAIJ format on one processor) 1971 1972 Notes: 1973 The user MUST specify either the local or global matrix dimensions 1974 (possibly both). 1975 1976 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1977 than it must be used on all processors that share the object for that argument. 1978 1979 Storage Information: 1980 For a square global matrix we define each processor's diagonal portion 1981 to be its local rows and the corresponding columns (a square submatrix); 1982 each processor's off-diagonal portion encompasses the remainder of the 1983 local matrix (a rectangular submatrix). 1984 1985 The user can specify preallocated storage for the diagonal part of 1986 the local submatrix with either d_nz or d_nnz (not both). Set 1987 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1988 memory allocation. Likewise, specify preallocated storage for the 1989 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1990 1991 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1992 the figure below we depict these three local rows and all columns (0-11). 1993 1994 .vb 1995 0 1 2 3 4 5 6 7 8 9 10 11 1996 ------------------- 1997 row 3 | o o o d d d o o o o o o 1998 row 4 | o o o d d d o o o o o o 1999 row 5 | o o o d d d o o o o o o 2000 ------------------- 2001 .ve 2002 2003 Thus, any entries in the d locations are stored in the d (diagonal) 2004 submatrix, and any entries in the o locations are stored in the 2005 o (off-diagonal) submatrix. Note that the d matrix is stored in 2006 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 2007 2008 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 2009 plus the diagonal part of the d matrix, 2010 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2011 In general, for PDE problems in which most nonzeros are near the diagonal, 2012 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2013 or you will get TERRIBLE performance; see the users' manual chapter on 2014 matrices. 2015 2016 Level: intermediate 2017 2018 .keywords: matrix, block, aij, compressed row, sparse, parallel 2019 2020 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 2021 @*/ 2022 2023 PetscErrorCode MatCreateMPISBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A) 2024 { 2025 PetscErrorCode ierr; 2026 PetscMPIInt size; 2027 2028 PetscFunctionBegin; 2029 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 2030 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2031 if (size > 1) { 2032 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 2033 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2034 } else { 2035 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 2036 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2037 } 2038 PetscFunctionReturn(0); 2039 } 2040 2041 2042 #undef __FUNCT__ 2043 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 2044 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2045 { 2046 Mat mat; 2047 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 2048 PetscErrorCode ierr; 2049 PetscInt len=0,nt,bs=matin->bs,mbs=oldmat->mbs; 2050 PetscScalar *array; 2051 2052 PetscFunctionBegin; 2053 *newmat = 0; 2054 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 2055 ierr = MatSetType(mat,matin->type_name);CHKERRQ(ierr); 2056 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2057 2058 mat->factor = matin->factor; 2059 mat->preallocated = PETSC_TRUE; 2060 mat->assembled = PETSC_TRUE; 2061 mat->insertmode = NOT_SET_VALUES; 2062 2063 a = (Mat_MPISBAIJ*)mat->data; 2064 mat->bs = matin->bs; 2065 a->bs2 = oldmat->bs2; 2066 a->mbs = oldmat->mbs; 2067 a->nbs = oldmat->nbs; 2068 a->Mbs = oldmat->Mbs; 2069 a->Nbs = oldmat->Nbs; 2070 2071 a->rstart = oldmat->rstart; 2072 a->rend = oldmat->rend; 2073 a->cstart = oldmat->cstart; 2074 a->cend = oldmat->cend; 2075 a->size = oldmat->size; 2076 a->rank = oldmat->rank; 2077 a->donotstash = oldmat->donotstash; 2078 a->roworiented = oldmat->roworiented; 2079 a->rowindices = 0; 2080 a->rowvalues = 0; 2081 a->getrowactive = PETSC_FALSE; 2082 a->barray = 0; 2083 a->rstart_bs = oldmat->rstart_bs; 2084 a->rend_bs = oldmat->rend_bs; 2085 a->cstart_bs = oldmat->cstart_bs; 2086 a->cend_bs = oldmat->cend_bs; 2087 2088 /* hash table stuff */ 2089 a->ht = 0; 2090 a->hd = 0; 2091 a->ht_size = 0; 2092 a->ht_flag = oldmat->ht_flag; 2093 a->ht_fact = oldmat->ht_fact; 2094 a->ht_total_ct = 0; 2095 a->ht_insert_ct = 0; 2096 2097 ierr = PetscMemcpy(a->rowners,oldmat->rowners,3*(a->size+2)*sizeof(PetscInt));CHKERRQ(ierr); 2098 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 2099 ierr = MatStashCreate_Private(matin->comm,matin->bs,&mat->bstash);CHKERRQ(ierr); 2100 if (oldmat->colmap) { 2101 #if defined (PETSC_USE_CTABLE) 2102 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2103 #else 2104 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2105 PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt)); 2106 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2107 #endif 2108 } else a->colmap = 0; 2109 2110 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2111 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2112 PetscLogObjectMemory(mat,len*sizeof(PetscInt)); 2113 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2114 } else a->garray = 0; 2115 2116 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2117 PetscLogObjectParent(mat,a->lvec); 2118 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2119 PetscLogObjectParent(mat,a->Mvctx); 2120 2121 ierr = VecDuplicate(oldmat->slvec0,&a->slvec0);CHKERRQ(ierr); 2122 PetscLogObjectParent(mat,a->slvec0); 2123 ierr = VecDuplicate(oldmat->slvec1,&a->slvec1);CHKERRQ(ierr); 2124 PetscLogObjectParent(mat,a->slvec1); 2125 2126 ierr = VecGetLocalSize(a->slvec1,&nt);CHKERRQ(ierr); 2127 ierr = VecGetArray(a->slvec1,&array);CHKERRQ(ierr); 2128 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,bs*mbs,array,&a->slvec1a);CHKERRQ(ierr); 2129 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec1b);CHKERRQ(ierr); 2130 ierr = VecRestoreArray(a->slvec1,&array);CHKERRQ(ierr); 2131 ierr = VecGetArray(a->slvec0,&array);CHKERRQ(ierr); 2132 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec0b);CHKERRQ(ierr); 2133 ierr = VecRestoreArray(a->slvec0,&array);CHKERRQ(ierr); 2134 PetscLogObjectParent(mat,a->slvec0); 2135 PetscLogObjectParent(mat,a->slvec1); 2136 PetscLogObjectParent(mat,a->slvec0b); 2137 PetscLogObjectParent(mat,a->slvec1a); 2138 PetscLogObjectParent(mat,a->slvec1b); 2139 2140 /* ierr = VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */ 2141 ierr = PetscObjectReference((PetscObject)oldmat->sMvctx);CHKERRQ(ierr); 2142 a->sMvctx = oldmat->sMvctx; 2143 PetscLogObjectParent(mat,a->sMvctx); 2144 2145 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2146 PetscLogObjectParent(mat,a->A); 2147 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2148 PetscLogObjectParent(mat,a->B); 2149 ierr = PetscFListDuplicate(mat->qlist,&matin->qlist);CHKERRQ(ierr); 2150 *newmat = mat; 2151 PetscFunctionReturn(0); 2152 } 2153 2154 #include "petscsys.h" 2155 2156 #undef __FUNCT__ 2157 #define __FUNCT__ "MatLoad_MPISBAIJ" 2158 PetscErrorCode MatLoad_MPISBAIJ(PetscViewer viewer,const MatType type,Mat *newmat) 2159 { 2160 Mat A; 2161 PetscErrorCode ierr; 2162 PetscInt i,nz,j,rstart,rend,fd; 2163 PetscScalar *vals,*buf; 2164 MPI_Comm comm = ((PetscObject)viewer)->comm; 2165 MPI_Status status; 2166 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 2167 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*browners,maxnz,*cols; 2168 PetscInt *locrowlens,*sndcounts = 0,*procsnz = 0,jj,*mycols,*ibuf; 2169 PetscInt bs=1,Mbs,mbs,extra_rows; 2170 PetscInt *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2171 PetscInt dcount,kmax,k,nzcount,tmp; 2172 2173 PetscFunctionBegin; 2174 ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 2175 2176 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2177 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2178 if (!rank) { 2179 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2180 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2181 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2182 if (header[3] < 0) { 2183 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2184 } 2185 } 2186 2187 ierr = MPI_Bcast(header+1,3,MPI_INT,0,comm);CHKERRQ(ierr); 2188 M = header[1]; N = header[2]; 2189 2190 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2191 2192 /* 2193 This code adds extra rows to make sure the number of rows is 2194 divisible by the blocksize 2195 */ 2196 Mbs = M/bs; 2197 extra_rows = bs - M + bs*(Mbs); 2198 if (extra_rows == bs) extra_rows = 0; 2199 else Mbs++; 2200 if (extra_rows &&!rank) { 2201 PetscLogInfo(0,"MatLoad_MPISBAIJ:Padding loaded matrix to match blocksize\n"); 2202 } 2203 2204 /* determine ownership of all rows */ 2205 mbs = Mbs/size + ((Mbs % size) > rank); 2206 m = mbs*bs; 2207 ierr = PetscMalloc(2*(size+2)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 2208 browners = rowners + size + 1; 2209 ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2210 rowners[0] = 0; 2211 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2212 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2213 rstart = rowners[rank]; 2214 rend = rowners[rank+1]; 2215 2216 /* distribute row lengths to all processors */ 2217 ierr = PetscMalloc((rend-rstart)*bs*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr); 2218 if (!rank) { 2219 ierr = PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2220 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2221 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2222 ierr = PetscMalloc(size*sizeof(PetscInt),&sndcounts);CHKERRQ(ierr); 2223 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2224 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2225 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2226 } else { 2227 ierr = MPI_Scatterv(0,0,0,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2228 } 2229 2230 if (!rank) { /* procs[0] */ 2231 /* calculate the number of nonzeros on each processor */ 2232 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2233 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2234 for (i=0; i<size; i++) { 2235 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2236 procsnz[i] += rowlengths[j]; 2237 } 2238 } 2239 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2240 2241 /* determine max buffer needed and allocate it */ 2242 maxnz = 0; 2243 for (i=0; i<size; i++) { 2244 maxnz = PetscMax(maxnz,procsnz[i]); 2245 } 2246 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2247 2248 /* read in my part of the matrix column indices */ 2249 nz = procsnz[0]; 2250 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2251 mycols = ibuf; 2252 if (size == 1) nz -= extra_rows; 2253 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2254 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2255 2256 /* read in every ones (except the last) and ship off */ 2257 for (i=1; i<size-1; i++) { 2258 nz = procsnz[i]; 2259 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2260 ierr = MPI_Send(cols,nz,MPI_INT,i,tag,comm);CHKERRQ(ierr); 2261 } 2262 /* read in the stuff for the last proc */ 2263 if (size != 1) { 2264 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2265 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2266 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2267 ierr = MPI_Send(cols,nz+extra_rows,MPI_INT,size-1,tag,comm);CHKERRQ(ierr); 2268 } 2269 ierr = PetscFree(cols);CHKERRQ(ierr); 2270 } else { /* procs[i], i>0 */ 2271 /* determine buffer space needed for message */ 2272 nz = 0; 2273 for (i=0; i<m; i++) { 2274 nz += locrowlens[i]; 2275 } 2276 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2277 mycols = ibuf; 2278 /* receive message of column indices*/ 2279 ierr = MPI_Recv(mycols,nz,MPI_INT,0,tag,comm,&status);CHKERRQ(ierr); 2280 ierr = MPI_Get_count(&status,MPI_INT,&maxnz);CHKERRQ(ierr); 2281 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2282 } 2283 2284 /* loop over local rows, determining number of off diagonal entries */ 2285 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 2286 odlens = dlens + (rend-rstart); 2287 ierr = PetscMalloc(3*Mbs*sizeof(PetscInt),&mask);CHKERRQ(ierr); 2288 ierr = PetscMemzero(mask,3*Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2289 masked1 = mask + Mbs; 2290 masked2 = masked1 + Mbs; 2291 rowcount = 0; nzcount = 0; 2292 for (i=0; i<mbs; i++) { 2293 dcount = 0; 2294 odcount = 0; 2295 for (j=0; j<bs; j++) { 2296 kmax = locrowlens[rowcount]; 2297 for (k=0; k<kmax; k++) { 2298 tmp = mycols[nzcount++]/bs; /* block col. index */ 2299 if (!mask[tmp]) { 2300 mask[tmp] = 1; 2301 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2302 else masked1[dcount++] = tmp; /* entry in diag portion */ 2303 } 2304 } 2305 rowcount++; 2306 } 2307 2308 dlens[i] = dcount; /* d_nzz[i] */ 2309 odlens[i] = odcount; /* o_nzz[i] */ 2310 2311 /* zero out the mask elements we set */ 2312 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2313 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2314 } 2315 2316 /* create our matrix */ 2317 ierr = MatCreate(comm,m,m,PETSC_DETERMINE,PETSC_DETERMINE,&A);CHKERRQ(ierr); 2318 ierr = MatSetType(A,type);CHKERRQ(ierr); 2319 ierr = MatMPISBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2320 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2321 2322 if (!rank) { 2323 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2324 /* read in my part of the matrix numerical values */ 2325 nz = procsnz[0]; 2326 vals = buf; 2327 mycols = ibuf; 2328 if (size == 1) nz -= extra_rows; 2329 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2330 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2331 2332 /* insert into matrix */ 2333 jj = rstart*bs; 2334 for (i=0; i<m; i++) { 2335 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2336 mycols += locrowlens[i]; 2337 vals += locrowlens[i]; 2338 jj++; 2339 } 2340 2341 /* read in other processors (except the last one) and ship out */ 2342 for (i=1; i<size-1; i++) { 2343 nz = procsnz[i]; 2344 vals = buf; 2345 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2346 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2347 } 2348 /* the last proc */ 2349 if (size != 1){ 2350 nz = procsnz[i] - extra_rows; 2351 vals = buf; 2352 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2353 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2354 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2355 } 2356 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2357 2358 } else { 2359 /* receive numeric values */ 2360 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2361 2362 /* receive message of values*/ 2363 vals = buf; 2364 mycols = ibuf; 2365 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2366 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2367 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2368 2369 /* insert into matrix */ 2370 jj = rstart*bs; 2371 for (i=0; i<m; i++) { 2372 ierr = MatSetValues_MPISBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2373 mycols += locrowlens[i]; 2374 vals += locrowlens[i]; 2375 jj++; 2376 } 2377 } 2378 2379 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2380 ierr = PetscFree(buf);CHKERRQ(ierr); 2381 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2382 ierr = PetscFree(rowners);CHKERRQ(ierr); 2383 ierr = PetscFree(dlens);CHKERRQ(ierr); 2384 ierr = PetscFree(mask);CHKERRQ(ierr); 2385 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2386 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2387 *newmat = A; 2388 PetscFunctionReturn(0); 2389 } 2390 2391 #undef __FUNCT__ 2392 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2393 /*@ 2394 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2395 2396 Input Parameters: 2397 . mat - the matrix 2398 . fact - factor 2399 2400 Collective on Mat 2401 2402 Level: advanced 2403 2404 Notes: 2405 This can also be set by the command line option: -mat_use_hash_table fact 2406 2407 .keywords: matrix, hashtable, factor, HT 2408 2409 .seealso: MatSetOption() 2410 @*/ 2411 PetscErrorCode MatMPISBAIJSetHashTableFactor(Mat mat,PetscReal fact) 2412 { 2413 PetscFunctionBegin; 2414 SETERRQ(PETSC_ERR_SUP,"Function not yet written for SBAIJ format"); 2415 /* PetscFunctionReturn(0); */ 2416 } 2417 2418 #undef __FUNCT__ 2419 #define __FUNCT__ "MatGetRowMax_MPISBAIJ" 2420 PetscErrorCode MatGetRowMax_MPISBAIJ(Mat A,Vec v) 2421 { 2422 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2423 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2424 PetscReal atmp; 2425 PetscReal *work,*svalues,*rvalues; 2426 PetscErrorCode ierr; 2427 PetscInt i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2428 PetscMPIInt rank,size; 2429 PetscInt *rowners_bs,dest,count,source; 2430 PetscScalar *va; 2431 MatScalar *ba; 2432 MPI_Status stat; 2433 2434 PetscFunctionBegin; 2435 ierr = MatGetRowMax(a->A,v);CHKERRQ(ierr); 2436 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2437 2438 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 2439 ierr = MPI_Comm_rank(A->comm,&rank);CHKERRQ(ierr); 2440 2441 bs = A->bs; 2442 mbs = a->mbs; 2443 Mbs = a->Mbs; 2444 ba = b->a; 2445 bi = b->i; 2446 bj = b->j; 2447 2448 /* find ownerships */ 2449 rowners_bs = a->rowners_bs; 2450 2451 /* each proc creates an array to be distributed */ 2452 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2453 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2454 2455 /* row_max for B */ 2456 if (rank != size-1){ 2457 for (i=0; i<mbs; i++) { 2458 ncols = bi[1] - bi[0]; bi++; 2459 brow = bs*i; 2460 for (j=0; j<ncols; j++){ 2461 bcol = bs*(*bj); 2462 for (kcol=0; kcol<bs; kcol++){ 2463 col = bcol + kcol; /* local col index */ 2464 col += rowners_bs[rank+1]; /* global col index */ 2465 for (krow=0; krow<bs; krow++){ 2466 atmp = PetscAbsScalar(*ba); ba++; 2467 row = brow + krow; /* local row index */ 2468 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2469 if (work[col] < atmp) work[col] = atmp; 2470 } 2471 } 2472 bj++; 2473 } 2474 } 2475 2476 /* send values to its owners */ 2477 for (dest=rank+1; dest<size; dest++){ 2478 svalues = work + rowners_bs[dest]; 2479 count = rowners_bs[dest+1]-rowners_bs[dest]; 2480 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,A->comm);CHKERRQ(ierr); 2481 } 2482 } 2483 2484 /* receive values */ 2485 if (rank){ 2486 rvalues = work; 2487 count = rowners_bs[rank+1]-rowners_bs[rank]; 2488 for (source=0; source<rank; source++){ 2489 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,A->comm,&stat);CHKERRQ(ierr); 2490 /* process values */ 2491 for (i=0; i<count; i++){ 2492 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2493 } 2494 } 2495 } 2496 2497 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2498 ierr = PetscFree(work);CHKERRQ(ierr); 2499 PetscFunctionReturn(0); 2500 } 2501 2502 #undef __FUNCT__ 2503 #define __FUNCT__ "MatRelax_MPISBAIJ" 2504 PetscErrorCode MatRelax_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2505 { 2506 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2507 PetscErrorCode ierr; 2508 PetscInt mbs=mat->mbs,bs=matin->bs; 2509 PetscScalar mone=-1.0,*x,*b,*ptr,zero=0.0; 2510 Vec bb1; 2511 2512 PetscFunctionBegin; 2513 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2514 if (bs > 1) 2515 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2516 2517 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2518 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2519 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2520 its--; 2521 } 2522 2523 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2524 while (its--){ 2525 2526 /* lower triangular part: slvec0b = - B^T*xx */ 2527 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2528 2529 /* copy xx into slvec0a */ 2530 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2531 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2532 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2533 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2534 2535 ierr = VecScale(&mone,mat->slvec0);CHKERRQ(ierr); 2536 2537 /* copy bb into slvec1a */ 2538 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2539 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 2540 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2541 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2542 2543 /* set slvec1b = 0 */ 2544 ierr = VecSet(&zero,mat->slvec1b);CHKERRQ(ierr); 2545 2546 ierr = VecScatterBegin(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2547 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2548 ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); 2549 ierr = VecScatterEnd(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2550 2551 /* upper triangular part: bb1 = bb1 - B*x */ 2552 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2553 2554 /* local diagonal sweep */ 2555 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2556 } 2557 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2558 } else { 2559 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2560 } 2561 PetscFunctionReturn(0); 2562 } 2563 2564 #undef __FUNCT__ 2565 #define __FUNCT__ "MatRelax_MPISBAIJ_2comm" 2566 PetscErrorCode MatRelax_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2567 { 2568 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2569 PetscErrorCode ierr; 2570 PetscScalar mone=-1.0; 2571 Vec lvec1,bb1; 2572 2573 PetscFunctionBegin; 2574 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2575 if (matin->bs > 1) 2576 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2577 2578 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2579 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2580 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2581 its--; 2582 } 2583 2584 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2585 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2586 while (its--){ 2587 ierr = VecScatterBegin(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2588 2589 /* lower diagonal part: bb1 = bb - B^T*xx */ 2590 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2591 ierr = VecScale(&mone,lvec1);CHKERRQ(ierr); 2592 2593 ierr = VecScatterEnd(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2594 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2595 ierr = VecScatterBegin(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2596 2597 /* upper diagonal part: bb1 = bb1 - B*x */ 2598 ierr = VecScale(&mone,mat->lvec);CHKERRQ(ierr); 2599 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2600 2601 ierr = VecScatterEnd(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2602 2603 /* diagonal sweep */ 2604 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2605 } 2606 ierr = VecDestroy(lvec1);CHKERRQ(ierr); 2607 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2608 } else { 2609 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2610 } 2611 PetscFunctionReturn(0); 2612 } 2613 2614